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Deep Gradient Compression: Reducing the Communication Bandwidth for
  Distributed Training
v1v2v3 (latest)

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

5 December 2017
Chengyue Wu
Song Han
Huizi Mao
Yu Wang
W. Dally
ArXiv (abs)PDFHTMLGithub (222★)

Papers citing "Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training"

50 / 625 papers shown
Title
Daydream: Accurately Estimating the Efficacy of Optimizations for DNN
  Training
Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training
Hongyu Zhu
Amar Phanishayee
Gennady Pekhimenko
145
50
0
05 Jun 2020
UVeQFed: Universal Vector Quantization for Federated Learning
UVeQFed: Universal Vector Quantization for Federated Learning
Nir Shlezinger
Mingzhe Chen
Yonina C. Eldar
H. Vincent Poor
Shuguang Cui
FedMLMQ
65
231
0
05 Jun 2020
Federated Learning for 6G Communications: Challenges, Methods, and
  Future Directions
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Yi Liu
Lizhen Qu
Zehui Xiong
Jiawen Kang
Xiaofei Wang
Dusit Niyato
FedMLAI4CE
70
283
0
04 Jun 2020
Local SGD With a Communication Overhead Depending Only on the Number of
  Workers
Local SGD With a Communication Overhead Depending Only on the Number of Workers
Artin Spiridonoff
Alexander Olshevsky
I. Paschalidis
FedML
61
19
0
03 Jun 2020
DaSGD: Squeezing SGD Parallelization Performance in Distributed Training
  Using Delayed Averaging
DaSGD: Squeezing SGD Parallelization Performance in Distributed Training Using Delayed Averaging
Q. Zhou
Yawen Zhang
Pengcheng Li
Xiaoyong Liu
Jun Yang
Runsheng Wang
Ru Huang
FedML
45
2
0
31 May 2020
rTop-k: A Statistical Estimation Approach to Distributed SGD
rTop-k: A Statistical Estimation Approach to Distributed SGD
L. P. Barnes
Huseyin A. Inan
Berivan Isik
Ayfer Özgür
75
65
0
21 May 2020
OD-SGD: One-step Delay Stochastic Gradient Descent for Distributed
  Training
OD-SGD: One-step Delay Stochastic Gradient Descent for Distributed Training
Yemao Xu
Dezun Dong
Weixia Xu
Xiangke Liao
47
7
0
14 May 2020
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized
  Optimization
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization
Navjot Singh
Deepesh Data
Jemin George
Suhas Diggavi
91
55
0
13 May 2020
Breaking (Global) Barriers in Parallel Stochastic Optimization with
  Wait-Avoiding Group Averaging
Breaking (Global) Barriers in Parallel Stochastic Optimization with Wait-Avoiding Group Averaging
Shigang Li
Tal Ben-Nun
Giorgi Nadiradze
Salvatore Di Girolamo
Nikoli Dryden
Dan Alistarh
Torsten Hoefler
75
15
0
30 Apr 2020
Memory-efficient training with streaming dimensionality reduction
Memory-efficient training with streaming dimensionality reduction
Siyuan Huang
Brian D. Hoskins
M. Daniels
M. D. Stiles
G. Adam
37
3
0
25 Apr 2020
A Review of Privacy-preserving Federated Learning for the
  Internet-of-Things
A Review of Privacy-preserving Federated Learning for the Internet-of-Things
Christopher Briggs
Zhong Fan
Péter András
133
15
0
24 Apr 2020
A Framework for Evaluating Gradient Leakage Attacks in Federated
  Learning
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
Wenqi Wei
Ling Liu
Margaret Loper
Ka-Ho Chow
Mehmet Emre Gursoy
Stacey Truex
Yanzhao Wu
FedML
111
150
0
22 Apr 2020
How to Train your DNN: The Network Operator Edition
How to Train your DNN: The Network Operator Edition
M. Chang
D. Bottini
Lisa Jian
Pranay Kumar
Aurojit Panda
S. Shenker
21
1
0
21 Apr 2020
Efficient Synthesis of Compact Deep Neural Networks
Efficient Synthesis of Compact Deep Neural Networks
Wenhan Xia
Hongxu Yin
N. Jha
62
3
0
18 Apr 2020
Detached Error Feedback for Distributed SGD with Random Sparsification
Detached Error Feedback for Distributed SGD with Random Sparsification
An Xu
Heng-Chiao Huang
71
9
0
11 Apr 2020
Client Selection and Bandwidth Allocation in Wireless Federated Learning
  Networks: A Long-Term Perspective
Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective
Jie Xu
Heqiang Wang
52
362
0
09 Apr 2020
Evaluating the Communication Efficiency in Federated Learning Algorithms
Evaluating the Communication Efficiency in Federated Learning Algorithms
Muhammad Asad
Ahmed Moustafa
Takayuki Ito
M. Aslam
FedML
65
55
0
06 Apr 2020
Reducing Data Motion to Accelerate the Training of Deep Neural Networks
Reducing Data Motion to Accelerate the Training of Deep Neural Networks
Sicong Zhuang
Cristiano Malossi
Marc Casas
34
0
0
05 Apr 2020
Scheduling for Cellular Federated Edge Learning with Importance and
  Channel Awareness
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness
Jinke Ren
Yinghui He
Dingzhu Wen
Guanding Yu
Kaibin Huang
Dongning Guo
108
197
0
01 Apr 2020
Edge Intelligence: Architectures, Challenges, and Applications
Edge Intelligence: Architectures, Challenges, and Applications
Dianlei Xu
Tong Li
Yong Li
Xiang Su
Sasu Tarkoma
Tao Jiang
Jon Crowcroft
Pan Hui
116
29
0
26 Mar 2020
FedSel: Federated SGD under Local Differential Privacy with Top-k
  Dimension Selection
FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection
Ruixuan Liu
Yang Cao
Masatoshi Yoshikawa
Hong Chen
FedML
67
108
0
24 Mar 2020
A Compressive Sensing Approach for Federated Learning over Massive MIMO
  Communication Systems
A Compressive Sensing Approach for Federated Learning over Massive MIMO Communication Systems
Yo-Seb Jeon
M. Amiri
Jun Li
H. Vincent Poor
70
9
0
18 Mar 2020
Communication-Efficient Distributed Deep Learning: A Comprehensive
  Survey
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey
Zhenheng Tang
Shaoshuai Shi
Wei Wang
Yue Liu
Xiaowen Chu
83
49
0
10 Mar 2020
Trends and Advancements in Deep Neural Network Communication
Trends and Advancements in Deep Neural Network Communication
Felix Sattler
Thomas Wiegand
Wojciech Samek
GNN
72
9
0
06 Mar 2020
Decentralized SGD with Over-the-Air Computation
Decentralized SGD with Over-the-Air Computation
Emre Ozfatura
Stefano Rini
Deniz Gunduz
70
38
0
06 Mar 2020
Communication optimization strategies for distributed deep neural
  network training: A survey
Communication optimization strategies for distributed deep neural network training: A survey
Shuo Ouyang
Dezun Dong
Yemao Xu
Liquan Xiao
123
12
0
06 Mar 2020
Distributed Momentum for Byzantine-resilient Learning
Distributed Momentum for Byzantine-resilient Learning
El-Mahdi El-Mhamdi
R. Guerraoui
Sébastien Rouault
FedML
58
22
0
28 Feb 2020
On Biased Compression for Distributed Learning
On Biased Compression for Distributed Learning
Aleksandr Beznosikov
Samuel Horváth
Peter Richtárik
M. Safaryan
81
189
0
27 Feb 2020
An On-Device Federated Learning Approach for Cooperative Model Update
  between Edge Devices
An On-Device Federated Learning Approach for Cooperative Model Update between Edge Devices
Rei Ito
Mineto Tsukada
Hiroki Matsutani
FedML
61
7
0
27 Feb 2020
LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient
  Distributed Learning
LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning
Tianyi Chen
Yuejiao Sun
W. Yin
FedML
47
14
0
26 Feb 2020
Optimal Gradient Quantization Condition for Communication-Efficient
  Distributed Training
Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training
An Xu
Zhouyuan Huo
Heng-Chiao Huang
MQ
40
6
0
25 Feb 2020
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees
Richeng Jin
Yufan Huang
Xiaofan He
H. Dai
Tianfu Wu
FedML
94
64
0
25 Feb 2020
Communication Contention Aware Scheduling of Multiple Deep Learning
  Training Jobs
Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs
Qiang-qiang Wang
Shaoshuai Shi
Canhui Wang
Xiaowen Chu
70
13
0
24 Feb 2020
Communication-Efficient Decentralized Learning with Sparsification and
  Adaptive Peer Selection
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection
Zhenheng Tang
Shaoshuai Shi
Xiaowen Chu
FedML
62
58
0
22 Feb 2020
Communication-Efficient Edge AI: Algorithms and Systems
Communication-Efficient Edge AI: Algorithms and Systems
Yuanming Shi
Kai Yang
Tao Jiang
Jun Zhang
Khaled B. Letaief
GNN
99
334
0
22 Feb 2020
Uncertainty Principle for Communication Compression in Distributed and
  Federated Learning and the Search for an Optimal Compressor
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
M. Safaryan
Egor Shulgin
Peter Richtárik
110
61
0
20 Feb 2020
MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for
  Personal Mobile Sensing
MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for Personal Mobile Sensing
Yu Zhang
Tao Gu
Xi Zhang
FedML
56
21
0
07 Feb 2020
Differentially Quantized Gradient Methods
Differentially Quantized Gradient Methods
Chung-Yi Lin
V. Kostina
B. Hassibi
MQ
66
8
0
06 Feb 2020
Communication Efficient Federated Learning over Multiple Access Channels
Communication Efficient Federated Learning over Multiple Access Channels
Wei-Ting Chang
Ravi Tandon
FedML
84
44
0
23 Jan 2020
Intermittent Pulling with Local Compensation for Communication-Efficient
  Federated Learning
Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
Yining Qi
Zhihao Qu
Song Guo
Xin Gao
Ruixuan Li
Baoliu Ye
FedML
45
9
0
22 Jan 2020
A Federated Deep Learning Framework for Privacy Preservation and
  Communication Efficiency
A Federated Deep Learning Framework for Privacy Preservation and Communication Efficiency
Tien-Dung Cao
Tram Truong-Huu
H. Tran
K. Tran
FedML
34
28
0
22 Jan 2020
Elastic Consistency: A General Consistency Model for Distributed
  Stochastic Gradient Descent
Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent
Giorgi Nadiradze
Ilia Markov
Bapi Chatterjee
Vyacheslav Kungurtsev
Dan Alistarh
FedML
121
14
0
16 Jan 2020
One-Bit Over-the-Air Aggregation for Communication-Efficient Federated
  Edge Learning: Design and Convergence Analysis
One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis
Guangxu Zhu
Yuqing Du
Deniz Gunduz
Kaibin Huang
107
317
0
16 Jan 2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An
  Online Learning Approach
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach
Pengchao Han
Shiqiang Wang
K. Leung
FedML
86
182
0
14 Jan 2020
Sparse Weight Activation Training
Sparse Weight Activation Training
Md Aamir Raihan
Tor M. Aamodt
142
73
0
07 Jan 2020
Think Locally, Act Globally: Federated Learning with Local and Global
  Representations
Think Locally, Act Globally: Federated Learning with Local and Global Representations
Paul Pu Liang
Terrance Liu
Liu Ziyin
Nicholas B. Allen
Randy P. Auerbach
David Brent
Ruslan Salakhutdinov
Louis-Philippe Morency
FedML
124
569
0
06 Jan 2020
Variance Reduced Local SGD with Lower Communication Complexity
Variance Reduced Local SGD with Lower Communication Complexity
Xian-Feng Liang
Shuheng Shen
Jingchang Liu
Zhen Pan
Enhong Chen
Yifei Cheng
FedML
95
154
0
30 Dec 2019
MG-WFBP: Merging Gradients Wisely for Efficient Communication in
  Distributed Deep Learning
MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning
Shaoshuai Shi
Xiaowen Chu
Bo Li
FedML
61
25
0
18 Dec 2019
Advances and Open Problems in Federated Learning
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedMLAI4CE
296
6,335
0
10 Dec 2019
Privacy-Preserving Blockchain Based Federated Learning with Differential
  Data Sharing
Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing
Anudit Nagar
51
21
0
10 Dec 2019
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